Scientific Visualization is one of the most interesting and challenging fields of science and technology.
In this post we would like to start a discussion on importance of the scientific visualization for science and technology. Here we share our thoughts about 3D computer graphics and we also quote the ideas of some prominent scientists.
With advances of digital instrumentation and computation technologies, the stream of scientific data for analysis is growing increasingly fast. Automatic data acquisition systems, scientific imaging, high performance digitizers, fast data interfaces, cluster processing, etc. all together can provide immense experimental raw material, that was not even dreamed about 10 years ago. On the other side the “visual human interface” between computer and scientist, in practice, did not changed that much. Scientific plotting remains basically the same for decades. In this respect the bottleneck in experimental data evaluation has moved from instrument to PC communication link to PC to scientist. In most of the experiments it is always desirable to have real-time feedback between Experimental Process via instruments and PC to Human and back.
In this respect, if some time ago doing “The Art of Science” was considered to assemble automated experiment set-up (data collection), now it is to deduct most useful information from massive data stream, make correct decision in real time and perform “Genius Touch” in experiment conditions adjustment that might reveal new law of nature. While the key of any experiment is the human brain, suitable visualization system can significantly simplify the job of the scientist. To be able to do so the visualization system must remove the routine observation of tables, multiple line plots and other low information graphical interface replacing that with multidimensional graphics that brings together all the data while emphasizing most important part of it.
The clear vision of visualization importance for science is expressed in the article published by Carol Cruzan Morton
http://ucdavismagazine.ucdavis.edu/issues/su97/Gallery/Gallery.html ,
where the author cites the ideas of Prof. Gergely Zimanyi at UC Davis.
Zimanyi predicts a new convergence of science and art with the latest technological changes made possible by computers. "When a modern scientist's program spews out a million data, in what sense is the problem solved?" he says. "Only visualization can possibly help in comprehending such a massive output. This is why many scientists are using computers to better visualize their work." "There is a genuine possibility that the century-old rift between science and art may again be narrowed, this time by the advent of computers and video techniques."
In the vision of Prof. Hanspeter Pfister from Mitsubishi Electric Research Laboratories (MERL) there is a big mistmach between nowadays data
Connecting Visualization to the Sciences
Modern science is faced with an embarrassing mismatch between how much data we
can measure and generate, and how much we have so far understood. Future
discoveries will require close collaboration between scientists and computer scientist,
and visualization plays an important role in providing unparalleled insight into scientific
data and problems. Unfortunately, creators of visualization technology are often
disconnected from the sciences, and scientists often do not have access to the latest
visualization technology.
NIH/NSF Workshop on Visualization Research Challenges, Position Statement, September 18, 2004
http://visual.nlm.nih.gov/evc/meetings/vrc2004/position_papers/pfister.pdf
Prof. Pfister has participated in preparation one of the most significant reports in recent years dedicated to computer visualization: NIH-NSF Visualization Research Challenges Report, see reference #1 below.
Prof. Pfister is also a stuff member of Harvard University Initiative in Innovative Computing Group (IIC), see reference #2 below.
ScienceGL Inc. indirectly participates to IIC activities with our joint project of development 4D data high performance cluster distributed processing and visualization software system.
REFERENCES:
#1. NIH-NSF Visualization Research Challenges Report
U.S. National Institutes of Health, Bethesda, MD, U.S.A., January 2006
Editors: C. Johnson, R. Moorhead, T. Munzner, H. Pfister, P. Rheingans, and T. S. Yoo
In this report, the authors describe some of the remarkable achievements that visualization enables and discuss the major obstacles blocking the discipline's advancement. Their findings and recommendations reflect not only information gathered from visualization and applications scientists during the two workshops on Visualization Research Challenges but also input from the larger visualization community.
#2. Harvard University Initiative in Innovative Computing Group (IIC)Overview
The Initiative in Innovative Computing fosters the creative use of computational resources to address issues at the forefront of data-intensive science. Focusing on interdisciplinary collaborations that span traditional academic boundaries, the IIC fosters the flow of ideas and inventions along the continuum from basic science to scientific computation to computational science to computer science.
Current Projects
-Astronomical Medicine
-The Connectome
-Data Intensive Science and High Capacity Scientific Databases
-Gene Pattern and the Virtual Data Center
-National Virtual Observatory Portal
-Computational Framework for Neuroinformatics and Genetics
-Image and Meaning
Future Projects
-Multiscale Hemodynamics
-Medical Treatment Outcomes Online
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